@incollection{CzarneckiFettke2021, author = {Czarnecki, Christian and Fettke, Peter}, title = {Robotic process automation : Positioning, structuring, and framing the work}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {978-3-11-067668-6 (Print)}, doi = {10.1515/9783110676693-202}, pages = {3 -- 24}, year = {2021}, abstract = {Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.}, language = {en} } @incollection{BensbergAuthCzarnecki2021, author = {Bensberg, Frank and Auth, Gunnar and Czarnecki, Christian}, title = {Finding the perfect RPA match : a criteria-based selection method for RPA solutions}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {978-3-11-067677-8}, doi = {10.1515/9783110676693-201}, pages = {47 -- 75}, year = {2021}, abstract = {The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.}, language = {en} } @incollection{CroonCzarnecki2021, author = {Croon, Philipp and Czarnecki, Christian}, title = {Liability for loss or damages caused by RPA}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {9783110676778}, doi = {10.1515/9783110676693-202}, pages = {135 -- 151}, year = {2021}, abstract = {Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today's corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.}, language = {en} } @incollection{SchneiderWisselinkNoelleetal.2020, author = {Schneider, Dominik and Wisselink, Frank and N{\"o}lle, Nikolai and Czarnecki, Christian}, title = {Influence of artificial intelligence on commercial interactions in the consumer market}, series = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder}, booktitle = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder}, editor = {Bruhn, Manfred and Hadwich, Karsten}, publisher = {Springer Gabler}, address = {Wiesbaden}, isbn = {978-3-658-30167-5 (Print)}, doi = {10.1007/978-3-658-30168-2_7}, pages = {183 -- 205}, year = {2020}, abstract = {Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.}, language = {en} } @incollection{BensbergBuscherCzarnecki2019, author = {Bensberg, Frank and Buscher, Gandalf and Czarnecki, Christian}, title = {Digital transformation and IT topics in the consulting industry: a labor market perspective}, series = {Advances in consulting research : recent findings and practical cases}, booktitle = {Advances in consulting research : recent findings and practical cases}, editor = {Nissen, Volker}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-95998-6}, doi = {10.1007/978-3-319-95999-3_16}, pages = {341 -- 357}, year = {2019}, abstract = {Information technologies, such as big data analytics, cloud computing, cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns.}, language = {en} } @incollection{SchmitzDietzeCzarnecki2019, author = {Schmitz, Manfred and Dietze, Christian and Czarnecki, Christian}, title = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, series = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, booktitle = {Enabling digital transformation through robotic process automation at Deutsche Telekom}, editor = {Urbach, Nils and R{\"o}glinger, Maximilian}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-95272-7}, doi = {10.1007/978-3-319-95273-4_2}, pages = {15 -- 33}, year = {2019}, abstract = {Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT's digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data.}, language = {en} } @incollection{Czarnecki2018, author = {Czarnecki, Christian}, title = {Establishment of a central process governance organization combined with operational process improvements : Insights from a BPM Project at a leading telecommunications operator in the Middle East}, series = {Business process management cases : digital innovation and business transformation in practice}, booktitle = {Business process management cases : digital innovation and business transformation in practice}, editor = {vom Brocke, Jan and Mendling, Jan}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-58306-8}, doi = {10.1007/978-3-319-58307-5}, pages = {57 -- 76}, year = {2018}, abstract = {Because of customer churn, strong competition, and operational inefficiencies, the telecommunications operator ME Telco (fictitious name due to confidentiality) launched a strategic transformation program that included a Business Process Management (BPM) project. Major problems were silo-oriented process management and missing cross-functional transparency. Process improvements were not consistently planned and aligned with corporate targets. Measurable inefficiencies were observed on an operational level, e.g., high lead times and reassignment rates of the incident management process.}, language = {en} } @incollection{LeiseAltherrSimonetal.2019, author = {Leise, Philipp and Altherr, Lena and Simon, Nicolai and Pelz, Peter F.}, title = {Finding global-optimal gearbox designs for battery electric vehicles}, series = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, booktitle = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-21802-7}, doi = {10.1007/978-3-030-21803-4_91}, pages = {916 -- 925}, year = {2019}, abstract = {In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.}, language = {en} } @incollection{StengerAltherrAbel2019, author = {Stenger, David and Altherr, Lena and Abel, Dirk}, title = {Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead}, series = {Operations Research Proceedings 2018}, booktitle = {Operations Research Proceedings 2018}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-18499-5 (Print)}, doi = {10.1007/978-3-030-18500-8_47}, pages = {379 -- 385}, year = {2019}, abstract = {In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.}, language = {en} } @incollection{PfetschAbeleAltherretal.2021, author = {Pfetsch, Marc E. and Abele, Eberhard and Altherr, Lena and B{\"o}lling, Christian and Br{\"o}tz, Nicolas and Dietrich, Ingo and Gally, Tristan and Geßner, Felix and Groche, Peter and Hoppe, Florian and Kirchner, Eckhard and Kloberdanz, Hermann and Knoll, Maximilian and Kolvenbach, Philip and Kuttich-Meinlschmidt, Anja and Leise, Philipp and Lorenz, Ulf and Matei, Alexander and Molitor, Dirk A. and Niessen, Pia and Pelz, Peter F. and Rexer, Manuel and Schmitt, Andreas and Schmitt, Johann M. and Schulte, Fiona and Ulbrich, Stefan and Weigold, Matthias}, title = {Strategies for mastering uncertainty}, series = {Mastering uncertainty in mechanical engineering}, booktitle = {Mastering uncertainty in mechanical engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-78353-2}, doi = {10.1007/978-3-030-78354-9_6}, pages = {365 -- 456}, year = {2021}, abstract = {This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.}, language = {en} }